Robot Programming by Demonstration (2008)
Billard, A., Calinon, S., Dillmann, R., Schaal, S.
Robot PbD started about 30 years ago, growing importantly during the past decade. The rationale for moving from purely preprogrammed robots to very flexible user-based interfaces for training the...
A framework integrating statistical and social cues to teach a humanoid robot new skills (2008)
Bringing robots as collaborative partners into homes presents various challenges to human-robot interaction. Robots will need to interact with untrained users in environments that are originally...
Dynamical System Modulation for Robot Learning via Kinesthetic Demonstrations (2008)
Hersch, M., Guenter, F., Calinon, S., Billard, A.
We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture, and correctly reproduce it despite changes...
On Learning, Representing and Generalizing a Task in a Humanoid Robot (2007)
Calinon, S., Guenter, F., Billard, A.
We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to...
Robot programming by demonstration (RPD) covers methods by which a robot learns new skills through human guidance. We present an interactive, multimodal RPD framework using active teaching methods...
Incremental Learning of Gestures by Imitation in a Humanoid Robot (2007)
We present an approach to teach incrementally human gestures to a humanoid robot. The learning process consists of first projecting the movement data in a latent space and encoding the resulting...
Learning of Gestures by Imitation in a Humanoid Robot (2007)
In this chapter, we explore the issue of encoding, recognizing, generalizing and reproducing arbitrary gestures. We address one major and generic issue, namely how to discover the essence of a...
Reinforcement Learning for Imitating Constrained Reaching Movements (2007)
Guenter, F., Hersch, M., Calinon, S., Billard, A.
The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots that can be accomplished by everyone. When a demonstrator teaches a task to a...
Active Teaching in Robot Programming by Demonstration (Ro- Man'2007 best paper award) (2007)
Robot Programming by Demonstration (RbD) covers methods by which a robot learns new skills through human guidance. In this work, we take the perspective that the role of the teacher is more important...
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts (2006)
Calinon, S., Guenter, F., Billard, A.
This paper presents an architecture for solving generically the problem of extracting the relevant features of a given task in a programming by demonstration framework and the problem of generalizing...
Teaching a Humanoid Robot to Recognize and Reproduce Social Cues (2006)
In a Robot Programming by Demonstration framework, several demonstrations of a task are required to generalize and reproduce the task under different circumstances. To teach a task to the robot,...
Learning Dynamical System Modulation for Constrained Reaching Tasks (2006)
Hersch, M., Guenter, F., Calinon, S., Billard, A.
In this paper we combine kinesthetic demonstrations and dynamical systems to enable a humanoid robot to imitate constrained reaching gestures directed toward a target. Using a learning algorithm...
Discriminative and Adaptive Imitation in Uni-Manual and Bi-Manual Tasks (2006)
Billard, A., Calinon, S., Guenter, F.
This paper addresses the problems of what to imitate and how to imitate in simple uni- and bi-manual manipulatory tasks. To solve the what to imitate issue, we use a probabilistic method, based on...
Trajectory Optimization by Constraints-Based Imitation (2005)
Guenter, F., Calinon, S., Billard, A.
Our work aims at developing a robust discriminant controller for robot programming by demonstration. When learning a new task by imitation, the robot must first determine what are the relevant...
Calinon, S., Billard, A., Dautenhahn, K., Nehaniv, C. L.
In this chapter, we explore the issue of encoding, recognizing, generalizing and reproducing arbitrary gestures. We address one major and generic issue, namely "how to discover the essence of a...
Goal-Directed Imitation in a Humanoid Robot (2005)
Calinon, S., Guenter, F., Billard, A.
Our work aims at developing a robust discriminant controller for robot programming by demonstration. It addresses two core issues of imitation learning, namely "what to imitate" and "how to imitate"....
This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the gesture and discards...
A Humanoid Robot Drawing Human Portraits (2005)
Calinon, S., Epiney, J., Billard, A.
This paper presents the creation of a robot capable of drawing artistic portraits. The application is purely entertaining and based on existing tools for face detection and image reconstruction, as...
Discovering Optimal Imitation Strategies (2004)
Billard, A., Epars, Y., Calinon, S., Cheng, G., Schaal, S.
This paper develops a general policy for learning relevant features of an imitation task. We restrict our study to imitation of manipulative tasks or of gestures. The imitation process is modeled as...
Stochastic Gesture Production and Recognition Model for a Humanoid Robot (2004)
Robot Programming by Demonstration (PbD) aims at developing adaptive and robust controllers to enable the robot to learn new skills by observing and imitating a human demonstration. While the vast...
PDA Interface for Humanoid Robots (2003)
To fulfill a need for natural, user-friendly means of interacting and reprogramming toy and humanoid robots, a growing trend of robotics research investigates the integration of methods for gesture...
A probabilistic approach to learn and reproduce dynamics of human motion by imitation
Calinon, S, Caldwell, D, Billard, A, D'halluin, F
We consider the problem of learning robust models of robot motion through demonstration, and present an approach based on Hidden Markov Model (HMM) and Gaussian Mixture Regression (GMR) to extract...